Neo-Classical Minimax Problems, Thresholding and Adaptive Function Estimation
نویسندگان
چکیده
منابع مشابه
Neo - Classical Minimax Problems , Thresholding , and Adaptation
We study the problem of estimating from data Y N( ; ) under squared-error loss. We de ne three new scalar minimax problems in which the risk is weighted by the size of . Simple thresholding gives asymptotically minimax estimates of all three problems. We indicate the relationships of the new problems to each other and to two other neo-classical problems: the problems of the bounded normal mean ...
متن کاملNeo - Classical Minimax Problems , Thresholding , and
We study the problem of estimating from data Y N(; 2) under squared-error loss. We deene three new scalar minimax problems in which the risk is weighted by the size of. Simple thresholding gives asymptotically minimax estimates of all three problems. We indicate the relationships of the new problems to each other and to two other neo-classical problems: the problems of the bounded normal mean a...
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Wavelet shrinkage methods have been very successful in nonparametric regression. The most commonly used wavelet procedures achieve adaptivity through term-by-term thresholding. The resulting estimators attain the minimax rates of convergence up to a logarithmic factor. In the present paper, we propose a block thresholding method where wavelet coef-cients are thresholded in blocks, rather than i...
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ژورنال
عنوان ژورنال: Bernoulli
سال: 1996
ISSN: 1350-7265
DOI: 10.2307/3318568